class_docstr: Generates snow effect on given tensor image or a batch tensor images.
  
  Args:
      snow_coefficient: A tuple of floats (lower and upper bound) between 0 and 1 that control
      the amount of snow to add to the image, the larger value corresponds to the more snow.
      brightness: A tuple of floats (lower and upper bound) greater than 1 that controls the
      brightness of the snow.
      same_on_batch: If True, apply the same transformation to each image in a batch. Default: False.
      p: Probability of applying the transformation. Default: 0.5.
      keepdim: Keep the output tensor with the same shape as input. Default: False.
  
  Shape:
      - Input: :math:`(C, H, W)` or :math:`(B, C, H, W)`
      - Output: :math:`(B, C, H, W)`
  
  Examples:
      >>> inputs = torch.rand(2, 3, 4, 4)
      >>> snow = kornia.augmentation.RandomSnow(p=1.0, snow_coefficient=(0.1, 0.6), brightness=(1.0, 5.0))
      >>> output = snow(inputs)
      >>> output.shape
      torch.Size([2, 3, 4, 4])
code: def __init__(
      self,
      snow_coefficient: Tuple[float, float] = (0.5, 0.5),
      brightness: Tuple[float, float] = (2, 2),
      same_on_batch: bool = False,
      p: float = 1.0,
      keepdim: bool = False,
  ) -> None:
      super().__init__(
          p=p, same_on_batch=same_on_batch, keepdim=keepdim
      )
      KORNIA_CHECK(
          all(0 <= el <= 1 for el in snow_coefficient),
          "Snow coefficient values must be between 0 and 1.",
      )
      KORNIA_CHECK(
          all(1 <= el for el in brightness),
          "Brightness values must be greater than 1.",
      )
  
      self._param_generator = rg.PlainUniformGenerator(
          (snow_coefficient, "snow_coefficient", 0.5, (0.0, 1.0)),
          (brightness, "brightness", None, None),
      )
  
file_path: kornia/kornia/augmentation/_2d/intensity/random_snow.py
imports: from typing import Any, Dict, Optional, Tuple
  import torch
  from kornia.augmentation import random_generator
  from kornia.augmentation._2d.intensity.base import IntensityAugmentationBase2D
  from kornia.color import hls_to_rgb, rgb_to_hls
  from kornia.core import Tensor
  from kornia.core.check import KORNIA_CHECK
label_desc: Use image node_id 1 to create a new RandomSnow object from inherited base classes: IntensityAugmentationBase2D with example: obj = RandomSnow(snow_coefficient, brightness, same_on_batch, p, keepdim)